This disclosure relates generally to the field of digital image processing. More particularly, but not by way of limitation, it relates to automatically adjusting the exposure of a digital image capture device by metering on multiple areas within an image. This application is related to the subject matter of the following commonly assigned applications: Ser. No. 12/755,542 filed Apr. 7, 2010; Ser. No. 12/786,710 filed May 25, 2010; Ser. No. 12/793,848 filed Jun. 4, 2010; and Ser. No. 12/912,943 filed Oct. 27, 2010 all of which are hereby incorporated by reference in their entirety.
Today, many personal electronic devices come equipped with digital cameras. Example personal electronic device of this sort include, but are not limited to, mobile telephones, personal digital assistants, portable music and video players and portable computer systems such as laptop, notebook and tablet computers. Often, these devices perform many functions, and, as a consequence, the digital image sensors included in these devices are often smaller than sensors in dedicated digital cameras. Further, the camera hardware in these devices often lacks sophisticated features sometimes found in larger, professional-style digital cameras such as manual exposure controls and manual focus. Thus, it is important that digital cameras in personal electronic devices be able to produce the most visually appealing images in a wide variety of lighting and scene situations with limited or no interaction from the user, as well as in a computationally and cost effective manner.
One feature that has been implemented in some digital cameras to create visually appealing images is known as “auto exposure.” Auto exposure (AE) can be defined generally as any operation that automatically calculates and/or manipulates certain camera exposure parameters, e.g., exposure time, gain, or f-number, in such a way that the currently exposed scene is captured in a desirable manner. For example, there may be a predetermined “optimum brightness value” for a given scene that the camera will try to achieve by adjusting the camera's exposure value (generally taken to be 18% gray). Some AE algorithms calculate and/or manipulate a camera's exposure parameters such that a mean, center-weighted mean, median, or more complicated weighted value (as in matrix metering) of the image's brightness will equal a predetermined optimum brightness value in the resultant, auto exposed scene (again, generally taken to be 18% gray). AE algorithms may also be aided by face detection technologies. In these auto exposure algorithms, a camera will attempt to locate one or more human faces within the scene and tailor its exposure and/or focus parameters to the location of the face or faces in the scene. Such algorithms account for the fact that a good assumption in most consumer photography is that human faces are often the desired subject in an image and, thus, focusing on and exposing properly such faces will often lead to visually pleasing images.
To date, however, AE operations used in personal electronic devices have yielded less than optimal results. By way of example, metering either a scene as a whole or concentrating only on faces (as noted above) can yield images that are washed out due to bright backgrounds or shiny faces, or under-exposed due to large areas of darkness. As a consequence, there is a need for improved auto-exposure operations.